With the increasing market demand, higher-end display equipment is needed in the field of high-end display particularly. Display resolution and display equipment dimension are gradually increased from the initial 480P kinescope televisions to subsequent display equipment with resolutions of 720P, FHD (full high definition), 2K, 4K, 8K, and the like.
In order to reduce the cost for running system and improve image quality, super resolution (SR) algorithms become current mainstream algorithms in the field of high-end display (for example, 4K2K), which means an operation for recovering low-resolution images or image sequences into high-resolution images.
The super resolution algorithms, which are technologies for enhancing the resolution of an image or a video, are designed for obtaining a clear high-resolution (HR) image from one or more low-resolution (LR) images by virtue of a corresponding algorithm. That is, the SR algorithms aim at causing the resolution of the output image or video to be higher than the resolution of any input image or any frame of the input video. The obtained HR image here means that the image has a high pixel density, and can provide more details.
However, with respect to actual product applications, most of the present SR algorithms have the defect of a high calculated amount, resulting in increased cost and low practicability, no that the present SR algorithms do not be applied to commercial video products. On the other hand, simple and rapid SR algorithms such as an adjacent substitution algorithm, a bilinear interpolation algorithm, a Hermite interpolation algorithm, and a Canny interpolation algorithm may cause the defects of sawtooth, blurring and the like on images.
Therefore, one of the tasks dedicated in the industry is to solve the above problems, so that the defects of sawtooth on an output image are obviously alleviated by a simple and fast algorithm, and thus the cost is reduced.